• Title/Summary/Keyword: 퍼지 평가

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Optimal Design of Interval Type-2 Fuzzy Set-based Multi-Output Fuzzy Neural Networks (다중 출력을 가지는 Interval Type-2 퍼지 집합 기반 퍼지 뉴럴 네트워크 최적 설계)

  • Park, Keon-Jun;Kim, Yong-Kab;Oh, Sung-Kwun;Kim, Hyun-Ki
    • Proceedings of the KIEE Conference
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    • 2011.07a
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    • pp.1968-1969
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    • 2011
  • 본 논문에서는 패턴 인식을 위한 다중 출력을 가지는 Interval Type-2 퍼지 집합을 이용한 퍼지 집합 기반 퍼지 뉴럴 네트워크를 소개한다. Interval Type-2 퍼지 집합 기반 퍼지 뉴럴 네트워크는 각 입력 변수에 따른 서로 분리된 입력 공간을 분할함으로서 네트워크 및 규칙을 구성한다. 규칙의 전반부는 퍼지 입력 공간을 개별적으로 분할하여 표현하고, 각 공간은 Interval Type-2 퍼지 집합으로 구성된다. 규칙의 후반부는 패턴 인식을 위한 다중 출력을 가지며 Interval 집합을 이용하여 다항식으로서 표현된다. 다항식의 계수인 연결가중치는 오류역 전파 알고리즘을 이용하여 학습한다. 또한 실수 코딩 유전자 알고리즘을 이용하여 제안된 네트워크를 최적화한다. 제안된 네트워크는 표준 모델로서 널리 사용되는 수치적인 예를 통하여 평가한다.

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Optimal Identification of Data Granules-based Fuzzy Set Fuzzy Model (데이터 입자 기반 퍼지 집합 퍼지 모델의 최적 동정)

  • Park Keon-Jun;Kim Wan-Su;Oh Sung-Kwun;Kim Hyun-Ki
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2005.04a
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    • pp.317-320
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    • 2005
  • 본 논문은 비선형 시스템의 퍼지모델을 설계하기 위해 데이터 입자 기반 퍼지 집합 퍼지 모델의 최적 동정을 제안한다. 퍼지모델은 주로 경험적 방법에 의해 추출되기 때문에 보다 구체적이고 체계적인 방법에 의한 동정 및 최적화 될 필요성이 요구된다. HCM 클러스터링을 통한 데이터 입자는 입력 변수의 개별적인 퍼지 규칙을 형성하고, 퍼지 공간 분할 및 삼각형 멤버쉽 함수의 초기 정점을 정의한다. 또한, 데이터 입자의 중심을 이용하여 후반부의 구조를 결정한다. 초기 퍼지 모델을 동정하기 위해 유전자 알고리즘을 이용하여 입력 변수의 수, 선택될 입력 변수, 멤버쉽 함수의 수, 그리고 후반부 형태를 결정한다. 데이터 입자에 의한 전반부 멤버쉽 파라미터는 유전자 알고리즘을 이용하여 최적으로 동정한다 제안된 모델을 평가하기 위해 수치적인 예를 사용한다.

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A Fuzzy Databased Models for Supporting Disjunctive Fuzzy Information (논리합 퍼지 부분 정보를 지원하는 퍼지 데이터베이스 모델)

  • Yang, Jae-Dong
    • Journal of KIISE:Software and Applications
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    • v.26 no.2
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    • pp.234-240
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    • 1999
  • 널값(null value)중 그 값은 존재하지만 현재 알려지지 않은 값을 미지 값(unknown value)이라고 한다. 본 논문에서는 논리합 퍼지 정보를 허용하는 퍼지 데이터베이스 응용 환경에서 잠재술어(Implicit Predicate, IP)를 이용하여 미지 값을 문제를 해결하기 위한 새로운 접근 방법을 제안한다. 이 방법의 특징은 첫째, 논리합 퍼지 정보를 퍼지 데이터베이스 내에 허용함으로써 미지 값의 의미적 표현력을 강화시키고, 둘째 개념에 기반한 퍼지 부합 매커니즘을 지원할 수 있으며, 셋째, 퍼지 소속성 함수를 구조화하여 시소러스로 활용함으로서 보다 정교한 부합을 가능하게 한다는 점 등이다. 본 논문에서는 먼저 이러한 IP의 특징들에 대해 기술하고 퍼지 데이터베이스에서 이 IP들을 최대한 이용하여 확정적 답을 이끌어 내기 위한 질의 평가 방식을 제안한다.

A Self-Organizing Fuzzy Logic Controller with a Performance Evaluation Level (성능평가 계층이 있는 자기구성 퍼지제어기)

  • 김동현;이평기;전기준
    • Journal of the Korean Institute of Intelligent Systems
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    • v.8 no.2
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    • pp.21-34
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    • 1998
  • [n this paper, we propose a hierarchical self-organizing fuzzy logic controller to improve the performance of the FARMA(Fuzzy auto-regressive moving average) SOC(Self-organizing fuzzy logic controller) when the system parameters change. The proposed controller contains the FARMA SC)C in the lower level and has a coordinator in the higher level, which evaluates convergence. and when it senses the degradation of system performance it compensates the control input by a look-up table. The proposed controller shows good perforniance over the FARMA SOC when the system parameters change. We executed some computer simulations on the regulation problem of an inlrerted pendulum system and compared the results with those of the FARMA SOC. As a result, it ha:; been shown that the proposed controller outperformed the FARMA SOC when the changes of the system parameters occurred.

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A Fuzzy Trust Model incorporating Dispositional Trust, General Trust, Situational Trust and Reputation (기질신뢰, 일반신뢰, 상황신뢰, 명성을 고려한 퍼지 신뢰모델)

  • Lee, Keon-Myung;Lee, Kyung-Mi
    • Journal of the Korean Institute of Intelligent Systems
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    • v.16 no.6
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    • pp.653-658
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    • 2006
  • Trust can be defined as the level of subjective probability with which an agent will perform a particular action. This paper proposes a comprehensive fuzzy trust model which incorporates dispositional trust, general trust, and situational trust and reputation information. In the model, the preference degrees for the interaction outcomes with respect to the evaluation criteria are expressed in a fuzzy set, and Sugeno's fuzzy integral is employed to aggregate the satisfaction degrees with respect to the importance of evaluation criteria which can be assigned in a way to preserve the properties of the ${\lambda}-fuzzy$ measure.

Partially Evaluated Genetic Algorithm based on Fuzzy Clustering (퍼지 클러스터링 기반의 국소평가 유전자 알고리즘)

  • Yoo Si-Ho;Cho Sung-Bae
    • Journal of KIISE:Software and Applications
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    • v.31 no.9
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    • pp.1246-1257
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    • 2004
  • To find an optimal solution with genetic algorithm, it is desirable to maintain the population sire as large as possible. In some cases, however, the cost to evaluate each individual is relatively high and it is difficult to maintain large population. To solve this problem we propose a novel genetic algorithm based on fuzzy clustering, which considerably reduces evaluation number without any significant loss of its performance by evaluating only one representative for each cluster. The fitness values of other individuals are estimated from the representative fitness values indirectly. We have used fuzzy c-means algorithm and distributed the fitness using membership matrix, since it is hard to distribute precise fitness values by hard clustering method to individuals which belong to multiple groups. Nine benchmark functions have been investigated and the results are compared to six hard clustering algorithms with Euclidean distance and Pearson correlation coefficients as fitness distribution method.

Implementation of Evaluation System of Water Quality for Branches of Geum River Using Fuzzy Integral (퍼지 적분을 이용한 금강지천의 수질오염 평가 시스템 구현)

  • Han, Seok-Soon;Kim, Hong-Ki;Lee, Kyung-Ho;Woo, Sun-Hee;Kim, Jai-Joung;Chung, Keun-Yook
    • The Journal of the Korea Contents Association
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    • v.6 no.10
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    • pp.1-8
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    • 2006
  • The new system evaluating the pollution of the water quality for the branches of geum river using the fuzzy integral was proposed in this study. In this paper, the five individual factors, such as BOD(biochemical oxygen demand), COD(chemical oxygen demand), SS(suspended solids), T-N(total nitrogen), and T-P(total phosphorus) are selected. The measurement of fuzzy integral was determined depending on the degree of how they affect the pollution of water quality. The real values for the five factors measured and obtained from the branches of the geum river was normalized to ranging from 0 to 1. Finally, using the fuzzy integral, the degree of the pollution for the branches of geum river was expressed as the real numerical number. As a result, it appears that this approach can be proposed as the new system evaluating the pollution of the water quality for the branches of the geum river.

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Priority Evaluation of Preliminary Cases for IMO Information Management System using Fuzzy TOPSIS and AHP (퍼지 TOPSIS&AHP를 이용한 IMO 정보관리시스템 예비과제 우선순위 평가)

  • Jang, Woon-Jae
    • Journal of Navigation and Port Research
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    • v.37 no.5
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    • pp.493-498
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    • 2013
  • This paper is aimed to priority evaluation of preliminary cases for IMO -IMS(International Maritime Organization- Information Management System) using fuzzy TOPSIS(Technique for Order Performance by Similarity to Ideal Solution) and AHP(Analytic Hierarchy Process). To this solve, therefore, this paper extract 24 preliminary cases and select 4 major preliminary alternative cases after analysing the structure of its alternative cases using FSM(Fuzzy Structure Modeling). Also, the weights of evaluation factors determine using AHP which able to keep the consistency when decision-makers assess. In AHP method, but, the numbers of paired comparison incerase as much as the numbers of the comparison items increase and because this evaluation have the many of vagueness, the decision of final ranking is used to fuzzy TOPSIS method which is included TOPSIS and Fuzzy Set Theory. The result are developed as order as Management of IMO Convention Information, Delivery of IMO Convention Information, Total IMO Database, Knowledge Hub of IMO Convention Information in IMO-IMS.

PCSI Evaluation System Based on Rough-Fuzzy Inference (러프-퍼지 추론기반 PCSI평가 시스템)

  • Kang, Jeon-Geun
    • Proceedings of the KAIS Fall Conference
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    • 2010.05a
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    • pp.89-91
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    • 2010
  • 본 논문에서는 학습에 임하는 학생과 교수자의 성향을 좀더 객관성 있게 검출, 면학 효과를 증진시키고자, 학습자와 교수자 상호 소통에 필요한 PCSI(Personal Coaching Styles Inventory)검사 모델을, 러프-퍼지 추론 기반에 의하여 평가하는 방법을 제안한다.

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Fuzzy Relation-Based Analysis of Korean Foods and Adjectives for Taste Evaluation (퍼지관계에 기반한 한국 음식과 맛 평가 형용사 분석)

  • Lee, Joonwhoan;Park, Keunho;Rho, Jeong-Ok
    • Journal of the Korean Institute of Intelligent Systems
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    • v.23 no.5
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    • pp.451-459
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    • 2013
  • In this paper we analyze the Korean foods and sensory adjectives that can be used for the taste expression of corresponding food based on the fuzzy relation. In order to construct fuzzy relation we gathered and chose 87 related Korean adjectives for expressing not only taste but also smell from foods. After then we performed a sensory evaluation for 51 Korean foods with 20 subjects to check the proper adjectives when they take a food. Based on the data collected by the evaluation a fuzzy relation is constructed and used for the analysis of the properties of food and adjectives. In addition the composition of the fuzzy relation provides the fuzzy tolerance(compatibility) relation among foods as well as that among adjectives. From the fuzzy complete ${\alpha}$-cover of the relations we could explore the taxonomy of food or adjectives. We expect that the fuzzy relation-based scheme in the paper can be utilized for analysis of the sensory adjectives like smelling and tactile sensation.